Background

Column

Concept

  • Browser-based dashboards and interactive visualizations are becoming increasingly common and accessible
  • With a relatively shallow learning-curve, an R user can use the flexdashboard, plotly and crosstalk packages to generate interactive dashboards for exploring data and models
  • The concept is demonstrated here using a simple data-set and linear regression; this can be extended to more complex cases

flexdashboard

  • Uses rmarkdown to render a group of related figures, tables and text into a dashboard
  • Layout is flexible and the components automatically resize to fill the browser and adapt to mobile displays
  • Supports a wide range of components, including base plot, ggplots, gauges, tables and htmlwidgets such as plotly
  • Optionally use shiny or crosstalk to bolster interactivity

Source: https://rmarkdown.rstudio.com/flexdashboard/

plotly

  • A graphing package that works like other R plots expect it produces interactive visualizations
  • The package allows the user to create interactive web graphics from ggplot2 graphs
  • Also provides a more ‘direct’ link to the core plotly.js JavaScript library using syntax inspired by the grammar of graphics

Source: https://plotly-r.com

crosstalk

  • Enables cross-widget interactions by linking brushing and/or filtering across multiple views
  • i.e. Interactions with one plot can affect change in another plot

Source: https://rstudio.github.io/crosstalk/

---
title: "Dashboards for stock assessments: Getting started"
output: 
  flexdashboard::flex_dashboard:
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
```


Background
===================================== 

Column {.tabset}
-------------------------------------

### Concept

- Browser-based dashboards and interactive visualizations are becoming increasingly common and accessible  
- With a relatively shallow learning-curve, an [**R**](https://www.r-project.org/) user can use the [**flexdashboard**](https://rmarkdown.rstudio.com/flexdashboard/), [**plotly**](https://plotly-r.com) and [**crosstalk**](https://rstudio.github.io/crosstalk/) packages to generate interactive dashboards for exploring data and models
- The concept is demonstrated here using a simple data-set and linear regression; this can be extended to more complex cases

### flexdashboard

- Uses [**rmarkdown**](https://rmarkdown.rstudio.com/) to render a group of related figures, tables and text into a dashboard  
- Layout is flexible and the components automatically resize to fill the browser and adapt to mobile displays
- Supports a wide range of components, including base plot, ggplots, gauges, tables and [htmlwidgets](http://www.htmlwidgets.org/index.html) such as [**plotly**](https://plotly-r.com)
- Optionally use [**shiny**](http://shiny.rstudio.com/) or [**crosstalk**](https://rstudio.github.io/crosstalk/) to bolster interactivity

> Source: https://rmarkdown.rstudio.com/flexdashboard/

### plotly

- A graphing package that works like other R plots expect it produces interactive visualizations
- The package allows the user to create interactive web graphics from [**ggplot2**](https://ggplot2.tidyverse.org/) graphs
- Also provides a more 'direct' link to the core [plotly.js](https://plot.ly/javascript/) JavaScript library using syntax inspired by the grammar of graphics

> Source: https://plotly-r.com

### crosstalk

- Enables cross-widget interactions by linking brushing and/or filtering across multiple views
- i.e. Interactions with one plot can affect change in another plot

> Source: https://rstudio.github.io/crosstalk/